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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base_lr_3e-4 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-base_lr_3e-4 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0682 |
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- Accuracy: 0.9784 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| 1.7893 | 0.9851 | 33 | 1.5529 | 0.4602 | |
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| 0.9637 | 2.0 | 67 | 0.8562 | 0.7563 | |
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| 0.5758 | 2.9851 | 100 | 0.4980 | 0.8276 | |
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| 0.5401 | 4.0 | 134 | 0.3442 | 0.8875 | |
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| 0.3908 | 4.9851 | 167 | 0.4630 | 0.8322 | |
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| 0.348 | 6.0 | 201 | 0.2102 | 0.9260 | |
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| 0.309 | 6.9851 | 234 | 0.1996 | 0.9391 | |
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| 0.305 | 8.0 | 268 | 0.3001 | 0.9185 | |
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| 0.2311 | 8.9851 | 301 | 0.2150 | 0.9335 | |
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| 0.2362 | 10.0 | 335 | 0.1218 | 0.9550 | |
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| 0.1929 | 10.9851 | 368 | 0.1334 | 0.9550 | |
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| 0.1781 | 12.0 | 402 | 0.1077 | 0.9597 | |
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| 0.15 | 12.9851 | 435 | 0.0749 | 0.9719 | |
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| 0.1437 | 14.0 | 469 | 0.0710 | 0.9756 | |
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| 0.1135 | 14.7761 | 495 | 0.0682 | 0.9784 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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